ny_times_us_counties
Data license: LICENSE · Data source: The New York Times · About: simonw/covid-19-datasette
61 rows where "date" is on date 2020-04-02 and state = "Pennsylvania" sorted by date descending
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fips >30
county >30
- Adams 1
- Allegheny 1
- Armstrong 1
- Beaver 1
- Bedford 1
- Berks 1
- Blair 1
- Bradford 1
- Bucks 1
- Butler 1
- Cambria 1
- Cameron 1
- Carbon 1
- Centre 1
- Chester 1
- Clarion 1
- Clearfield 1
- Columbia 1
- Crawford 1
- Cumberland 1
- Dauphin 1
- Delaware 1
- Erie 1
- Fayette 1
- Forest 1
- Franklin 1
- Greene 1
- Huntingdon 1
- Indiana 1
- Juniata 1
- …
state 1
- Pennsylvania · 61 ✖
Link | rowid | date ▲ | county | state | fips | cases | deaths |
---|---|---|---|---|---|---|---|
27758 | 27758 | 2020-04-02 | Adams | Pennsylvania | 42001 | 18 | 0 |
27759 | 27759 | 2020-04-02 | Allegheny | Pennsylvania | 42003 | 419 | 2 |
27760 | 27760 | 2020-04-02 | Armstrong | Pennsylvania | 42005 | 7 | 0 |
27761 | 27761 | 2020-04-02 | Beaver | Pennsylvania | 42007 | 55 | 2 |
27762 | 27762 | 2020-04-02 | Bedford | Pennsylvania | 42009 | 3 | 0 |
27763 | 27763 | 2020-04-02 | Berks | Pennsylvania | 42011 | 168 | 1 |
27764 | 27764 | 2020-04-02 | Blair | Pennsylvania | 42013 | 6 | 0 |
27765 | 27765 | 2020-04-02 | Bradford | Pennsylvania | 42015 | 8 | 0 |
27766 | 27766 | 2020-04-02 | Bucks | Pennsylvania | 42017 | 370 | 6 |
27767 | 27767 | 2020-04-02 | Butler | Pennsylvania | 42019 | 69 | 2 |
27768 | 27768 | 2020-04-02 | Cambria | Pennsylvania | 42021 | 4 | 0 |
27769 | 27769 | 2020-04-02 | Cameron | Pennsylvania | 42023 | 1 | 0 |
27770 | 27770 | 2020-04-02 | Carbon | Pennsylvania | 42025 | 26 | 1 |
27771 | 27771 | 2020-04-02 | Centre | Pennsylvania | 42027 | 28 | 0 |
27772 | 27772 | 2020-04-02 | Chester | Pennsylvania | 42029 | 210 | 2 |
27773 | 27773 | 2020-04-02 | Clarion | Pennsylvania | 42031 | 4 | 0 |
27774 | 27774 | 2020-04-02 | Clearfield | Pennsylvania | 42033 | 4 | 0 |
27775 | 27775 | 2020-04-02 | Columbia | Pennsylvania | 42037 | 11 | 0 |
27776 | 27776 | 2020-04-02 | Crawford | Pennsylvania | 42039 | 5 | 0 |
27777 | 27777 | 2020-04-02 | Cumberland | Pennsylvania | 42041 | 41 | 1 |
27778 | 27778 | 2020-04-02 | Dauphin | Pennsylvania | 42043 | 67 | 1 |
27779 | 27779 | 2020-04-02 | Delaware | Pennsylvania | 42045 | 470 | 8 |
27780 | 27780 | 2020-04-02 | Erie | Pennsylvania | 42049 | 16 | 0 |
27781 | 27781 | 2020-04-02 | Fayette | Pennsylvania | 42051 | 15 | 1 |
27782 | 27782 | 2020-04-02 | Forest | Pennsylvania | 42053 | 1 | 0 |
27783 | 27783 | 2020-04-02 | Franklin | Pennsylvania | 42055 | 23 | 0 |
27784 | 27784 | 2020-04-02 | Greene | Pennsylvania | 42059 | 11 | 0 |
27785 | 27785 | 2020-04-02 | Huntingdon | Pennsylvania | 42061 | 2 | 0 |
27786 | 27786 | 2020-04-02 | Indiana | Pennsylvania | 42063 | 6 | 0 |
27787 | 27787 | 2020-04-02 | Juniata | Pennsylvania | 42067 | 3 | 0 |
27788 | 27788 | 2020-04-02 | Lackawanna | Pennsylvania | 42069 | 108 | 3 |
27789 | 27789 | 2020-04-02 | Lancaster | Pennsylvania | 42071 | 203 | 4 |
27790 | 27790 | 2020-04-02 | Lawrence | Pennsylvania | 42073 | 16 | 2 |
27791 | 27791 | 2020-04-02 | Lebanon | Pennsylvania | 42075 | 45 | 0 |
27792 | 27792 | 2020-04-02 | Lehigh | Pennsylvania | 42077 | 479 | 5 |
27793 | 27793 | 2020-04-02 | Luzerne | Pennsylvania | 42079 | 384 | 5 |
27794 | 27794 | 2020-04-02 | Lycoming | Pennsylvania | 42081 | 7 | 0 |
27795 | 27795 | 2020-04-02 | McKean | Pennsylvania | 42083 | 1 | 0 |
27796 | 27796 | 2020-04-02 | Mercer | Pennsylvania | 42085 | 9 | 0 |
27797 | 27797 | 2020-04-02 | Mifflin | Pennsylvania | 42087 | 2 | 0 |
27798 | 27798 | 2020-04-02 | Monroe | Pennsylvania | 42089 | 321 | 10 |
27799 | 27799 | 2020-04-02 | Montgomery | Pennsylvania | 42091 | 735 | 9 |
27800 | 27800 | 2020-04-02 | Montour | Pennsylvania | 42093 | 15 | 0 |
27801 | 27801 | 2020-04-02 | Northampton | Pennsylvania | 42095 | 378 | 9 |
27802 | 27802 | 2020-04-02 | Northumberland | Pennsylvania | 42097 | 8 | 0 |
27803 | 27803 | 2020-04-02 | Perry | Pennsylvania | 42099 | 3 | 0 |
27804 | 27804 | 2020-04-02 | Philadelphia | Pennsylvania | 42101 | 1852 | 14 |
27805 | 27805 | 2020-04-02 | Pike | Pennsylvania | 42103 | 68 | 1 |
27806 | 27806 | 2020-04-02 | Potter | Pennsylvania | 42105 | 2 | 0 |
27807 | 27807 | 2020-04-02 | Schuylkill | Pennsylvania | 42107 | 54 | 0 |
27808 | 27808 | 2020-04-02 | Snyder | Pennsylvania | 42109 | 3 | 1 |
27809 | 27809 | 2020-04-02 | Somerset | Pennsylvania | 42111 | 3 | 0 |
27810 | 27810 | 2020-04-02 | Susquehanna | Pennsylvania | 42115 | 3 | 0 |
27811 | 27811 | 2020-04-02 | Tioga | Pennsylvania | 42117 | 2 | 0 |
27812 | 27812 | 2020-04-02 | Union | Pennsylvania | 42119 | 4 | 0 |
27813 | 27813 | 2020-04-02 | Venango | Pennsylvania | 42121 | 3 | 0 |
27814 | 27814 | 2020-04-02 | Warren | Pennsylvania | 42123 | 1 | 0 |
27815 | 27815 | 2020-04-02 | Washington | Pennsylvania | 42125 | 38 | 0 |
27816 | 27816 | 2020-04-02 | Wayne | Pennsylvania | 42127 | 17 | 0 |
27817 | 27817 | 2020-04-02 | Westmoreland | Pennsylvania | 42129 | 84 | 0 |
27818 | 27818 | 2020-04-02 | York | Pennsylvania | 42133 | 102 | 1 |
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CREATE TABLE [ny_times_us_counties] ( [date] TEXT, [county] TEXT, [state] TEXT, [fips] INTEGER, [cases] INTEGER, [deaths] INTEGER ); CREATE INDEX [idx_ny_times_us_counties_state] ON [ny_times_us_counties] ([state]); CREATE INDEX [idx_ny_times_us_counties_county] ON [ny_times_us_counties] ([county]); CREATE INDEX [idx_ny_times_us_counties_fips] ON [ny_times_us_counties] ([fips]); CREATE INDEX [idx_ny_times_us_counties_date] ON [ny_times_us_counties] ([date] desc);